DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. But first, let’s define the data mesh design pattern. The past decades of enterprise data platform architectures can be summarized in 69 words.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

IBM Big Data Hub

JUNE 8, 2022

Implementing the right data strategy spurs innovation and outstanding business outcomes by recognizing data as a critical asset that provides insights for better and more informed decision-making. By taking advantage of data, enterprises can shape business decisions, minimize risk for stakeholders, and gain competitive advantage.

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Data-driven Enterprise Data Governance Data Lake 56

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 84

Enterprise Data Warehouse Snapshot Cost-Benefit 84

Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

AWS Big Data

MARCH 7, 2023

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

Ontotext

NOVEMBER 16, 2023

Clarifying what data mesh is and how it works is important, but even more so is starting with the why. Why Organizations Need A Data Mesh The data mesh paradigm aims to address some of the biggest pain points for most organizations. This becomes particularly problematic when dealing with veracity of data.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Ontotext

FEBRUARY 12, 2024

As discussed in part one, the data mesh paradigm is still a relatively new concept with implementations in the early stages. Most enterprises have years of legacy systems, processes, and practices that make it more demanding to quickly jump onto the data mesh bandwagon. For instance, JPMorgan Chase & Co.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

Alation

APRIL 18, 2023

For any data user in an enterprise today, data profiling is a key tool for resolving data quality issues and building new data solutions. In this blog, we’ll cover the definition of data profiling, top use cases, and share important techniques and best practices for data profiling today.

IT 52

IT Metadata Data Quality Data Governance 52

Ontotext

MARCH 8, 2023

Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Each team and system need to keep diverse sets of data about their customers in order to play their specific role – inadvertently leading to siloed experiences. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Timo Elliott

DECEMBER 14, 2022

Gartner calls it the Composable Enterprise , for example – it’s about having a solid information foundation that enables fast and flexible creation of what they call composable applications that allow you to create new applications and workflows by just bringing together modular components. Business Process.

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Data Lake Recreation/Entertainment Metadata Data Warehouse 105

CIO Business Intelligence

APRIL 29, 2022

This would be straightforward task were it not for the fact that, during the digital-era, there has been an explosion of data – collected and stored everywhere – much of it poorly governed, ill-understood, and irrelevant. Further, data management activities don’t end once the AI model has been developed. Addressing the Challenge.

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Data Governance IT Risk Data Lake 144

Alation

FEBRUARY 13, 2020

Why do we need a data catalog? What does a data catalog do? These are all good questions and a logical place to start your data cataloging journey. Data catalogs have become the standard for metadata management in the age of big data and self-service analytics. Figure 1 – Data Catalog Metadata Subjects.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. So questions linger about whether transformed data can be trusted. Data Quality Obstacles.

Data Governance 40

Data Governance Risk Metadata Management 40

Alation

MARCH 22, 2022

As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT. Simply put, IDF standardizes data engineering processes. DataOps has emerged as an exciting solution. Transparency is key.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

bridgei2i

MARCH 11, 2021

With improved data cataloging functionality, their systems can become responsive. It’ll become easier to store metadata (data lakes, warehouses, data quality systems, etc.) Over time, as more data is constantly fed to the responsive system, ML algorithms improve their efficiency. in the system.

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Key Performance Indicator Data Governance Data Lake Metadata 52

Alation

NOVEMBER 28, 2022

Spreadsheet users can now pull high-quality data, with a view into its context and history, directly from Alation into Google Sheets. Talo: They say spreadsheets are “the dark matter” of the enterprise. Krishna: Spreadsheets are truly the dark matter of the data universe. What problems do spreadsheets create?

Metadata 52

Metadata Enterprise Cost-Benefit Finance 52

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Overlapping with the above, from around 2012, I began to get involved in also designing and implementing Big Data Architectures; initially for narrow purposes and later Data Lakes spanning entire enterprises.

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Data Lake Data Warehouse Data mining Statistics 63

Alation

JUNE 14, 2021

Indeed, automation is a key element to data catalog features, which enhance data security. Selecting a Data Catalog. To support data security, an effective data catalog should have features, like a business glossary, wiki-like articles, and metadata management. And, finding data is only half the battle.

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Data Governance Recreation/Entertainment Data Lake Digital Transformation 97

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

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Data Lake Metadata Data Warehouse Data Governance 52

Alation

JANUARY 26, 2023

However, data needs to be easily accessible, usable, and secure to be useful — yet the opposite is too often the case. What’s worse, just 3% of the data in a business enterprise meets quality standards. There’s also no denying that data management is becoming more important, especially to the public.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Peter James Thomas

AUGUST 29, 2018

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.

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Data-driven Cost-Benefit Metadata Technology 61

Octopai

JUNE 30, 2022

Establishing a single, enterprise-wide source of truth? Increasing data quality and accuracy? Why are data catalog use cases so downright… predictable? Here are three ways enterprises can leverage their data catalogs that don’t make the standard lists. The data catalog as an HR tool? Yeah, yeah.

Enterprise 72

Enterprise Data-driven Data Lake Data Quality 72

Ontotext

FEBRUARY 12, 2024

Although the enterprise data landscape is littered with new data technology and offerings, the most pressing problem data teams face today isn’t a lack of technology or skills; it’s not knowing how to create a modern data experience. They cover the utilization of data and specify the required data quality.

IT 64

IT Metadata Data Quality Data Lake 64

AWS Big Data

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

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Data Lake Data Warehouse Management Risk 100

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

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Data Lake Unstructured Data Data Warehouse Data Quality 105

Cloudera

DECEMBER 15, 2022

Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), Cloudera customers, such as Teranet , have built open lakehouses to future-proof their data platforms for all their analytical workloads. Only metadata will be regenerated. Data quality using table rollback.

Metadata 82

Metadata Data Warehouse Snapshot Data Quality 82

Cloudera

AUGUST 30, 2022

For state and local agencies, data silos create compounding problems: Inaccessible or hard-to-access data creates barriers to data-driven decision making. Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Towards Data Science ). Forrester ).

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Data Architecture Data Lake Metadata Data Warehouse 82

Alation

JANUARY 13, 2022

Thoughtworks says data mesh is key to moving beyond a monolithic data lake. Spoiler alert: data fabric and data mesh are independent design concepts that are, in fact, quite complementary. Thoughtworks says data mesh is key to moving beyond a monolithic data lake 2. Gartner on Data Fabric.

Data Lake 59

Data Lake Metadata Data-driven Data Governance 59

Alation

AUGUST 11, 2022

Today, the brightest minds in our industry are targeting the massive proliferation of data volumes and the accompanying but hard-to-find value locked within all that data. We chatted about industry trends, why decentralization has become a hot topic in the data world, and how metadata drives many data-centric use cases.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

Alation

JULY 19, 2022

A data catalog can assist directly with every step, but model development. And even then, information from the data catalog can be transferred to a model connector , allowing data scientists to benefit from curated metadata within those platforms. How Data Catalogs Help Data Scientists Ask Better Questions.

Metadata 59

Metadata Data Quality Statistics Data Science 59

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

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Management Metadata Data Architecture Data Lake 80

CIO Business Intelligence

JANUARY 30, 2024

Birgit Fridrich, who joined Allianz as sustainability manager responsible for ESG reporting in late 2022, spends many hours validating data in the company’s Microsoft Sustainability Manager tool. Data quality is key, but if we’re doing it manually there’s the potential for mistakes.

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Reporting Data Quality Strategy Data-driven 103

Cloudera

AUGUST 4, 2021

Not only is it critical to protect data, but data governance is also the foundation for data-driven businesses and maximizing value from data analytics. As a result, it’s easier to find people to handle highly routine-oriented data governance positions. This all requires a proactive governance strategy.

Data Governance 89

Data Governance Metadata Data-driven Enterprise 89

AWS Big Data

DECEMBER 18, 2023

Solution overview One of the common functionalities involved in data pipelines is extracting data from multiple data sources and exporting it to a data lake or synchronizing the data to another database. There are multiple tables related to customers and order data in the RDS database.

Metadata 121

Metadata Visualization Data Lake Data-driven 121

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. Then, you transform this data into a concise format.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69